361 citations · 1.2k across the 40 of their papers we have counts for
3 papers · 1 filter
Global field reconstruction from sparse sensors with Voronoi tessellation-assisted deep learning
Kai Fukami, Romit Maulik, Nesar Ramachandra +2
Achieving accurate and robust global situational awareness of a complex time-evolving field from a limited number of sensors has been a longstanding challenge. This reconstruction…
Probabilistic neural network-based reduced-order surrogate for fluid flows
Kai Fukami, Romit Maulik, Nesar Ramachandra +2
In recent years, there have been a surge in applications of neural networks (NNs) in physical sciences. Although various algorithmic advances have been proposed, there are, thus fa…
Probabilistic neural networks for fluid flow surrogate modeling and data recovery
Romit Maulik, Kai Fukami, Nesar Ramachandra +2
We consider the use of probabilistic neural networks for fluid flow {surrogate modeling} and data recovery. This framework is constructed by assuming that the target variables are…